Crop yield densities are often estimated at the county level. However, county-level yield data providers often omit county records due to low participation or other reasons. The data omission can undermine insurance premiumsÕ credibility and thereby lead to restrictions on the provision of area insurance products in specific locations. To address this problem, we propose a novel Bayesian spatial interpolation method to estimate crop yield densities for counties with missing data. Empirical results indicate that our approach is consistently superior to the benchmark approaches. Importantly, our approach offers noticeable estimation accuracy even at a significant level of data omission.